Integration of Safety Knowledge into Three-Dimensional Model Design and Construction Plan from the Perspective of Project Executors in Petrochemical Industry
Bibliographic record
Abstract
In petrochemical industry, the execution of construction involves three main issues, namely, design planning, construction, and job safety. Three-dimensional (3D) models are increasingly applied to design and construction. However, the improper concept of 3D design has bred potential unsatisfactory behaviors and the lack of vigilance among workers. Besides, many employees are not fully aware of the safety in 3D design and construction planning. Therefore, our goal is to improve the safety and health of construction workers through design practices in the upstream of the construction phase, and verify the applicability of the combination of 3D models and safety knowledge. Specifically, a questionnaire survey was carried out among 124 employees in the construction-related fields of the petrochemical industry. The collected data were processed, and statically analyzed on SPSS. The results show that safety knowledge was acceptable in 3D model design from the perspective of project executors, and the integration of safety knowledge into the design helps to improve the safety environment of the construction site.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".